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AI for Computational Audition: Sound and Music Processing

Artificial intelligence (AI) technology has promoted the transformation of traditional audio technology to intelligence. Using these emerging technologies to innovate and develop audio production and processing methods has become a key research direction in the field of computational audition. In recent years, AI technologies, such as deep learning, is becoming increasingly ubiquitous in the music industry, empowering music experimentation and has led to major progress in the innovation and development of audio production and reproduction technologies. 

Nowadays, the application of AI algorithms and techniques is ubiquitous and transversal. Fields that take advantage of AI advances include Sound and Music Processing. The advances in interdisciplinary research potentially yield new insights that may further advance the AI methods in this field. This special issue aims to spur new research lines in AI-driven sound and music processing, especially within interdisciplinary research scenarios. 

This special issue aims to collect research on AI for computational audition with a focus on music. The principal goal is to bring together scholars interested in the research on the theory and technology to realize the integration of traditional method and emerging technologies, the application and comparative analysis of different intelligent technologies in music creation.

Lead Guest Editor
Zijin Li, Central Conservatory of Music, China

Guest Editors
Wenwu Wang, University of Surrey, UK 
Kejun Zhang, Zhejiang University, China 
Mengyao Zhu, Shanghai University, China

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